





import warnings
from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


SCREAMING_SNAKE_CASE_   :      str			=   logging.get_logger(__name__)

class 		snake_case_   (							__lowercase						):







	'''simple docstring'''
	__UpperCamelCase   =		['''input_ids''', '''attention_mask''']




	def __init__(						self							:     Tuple					,      __lowerCamelCase							:     List[Any]="</s>"					,      __lowerCamelCase							:     str="<unk>"					,      __lowerCamelCase							:     int="<pad>"					,      __lowerCamelCase							:     Optional[int]=125					,      __lowerCamelCase							:     List[Any]=None					,      **__lowerCamelCase							:     Any					,      )       -> None:

			'''simple docstring'''




			if extra_ids > 0 and additional_special_tokens is None:
					__lowercase											=     [F"<extra_id_{i}>" for i in range(__lowerCamelCase   )]
			elif extra_ids > 0 and additional_special_tokens is not None:
					# Check that we have the right number of extra_id special tokens
					__lowercase											=     len(set(filter(lambda __lowerCamelCase   : bool('extra_id' in str(__lowerCamelCase   )   )					,      __lowerCamelCase   )   )   )
					if extra_tokens != extra_ids:
							raise ValueError(
							    F"Both extra_ids ({extra_ids}) and additional_special_tokens ({additional_special_tokens}) are"
							    ' provided to ByT5Tokenizer. In this case the additional_special_tokens must include the'
							    ' extra_ids tokens'   )

			__lowercase											=     AddedToken(__lowerCamelCase					,      lstrip=__lowerCamelCase					,      rstrip=__lowerCamelCase   ) if isinstance(__lowerCamelCase					,      __lowerCamelCase   ) else pad_token
			__lowercase											=     AddedToken(__lowerCamelCase					,      lstrip=__lowerCamelCase					,      rstrip=__lowerCamelCase   ) if isinstance(__lowerCamelCase					,      __lowerCamelCase   ) else eos_token
			__lowercase											=     AddedToken(__lowerCamelCase					,      lstrip=__lowerCamelCase					,      rstrip=__lowerCamelCase   ) if isinstance(__lowerCamelCase					,      __lowerCamelCase   ) else unk_token

			super().__init__(
			    eos_token=__lowerCamelCase					,      unk_token=__lowerCamelCase					,      pad_token=__lowerCamelCase					,      extra_ids=__lowerCamelCase					,      additional_special_tokens=__lowerCamelCase					,      **__lowerCamelCase					,      )

			__lowercase											=     extra_ids

			__lowercase											=     2**8  # utf is 8 bits

			# define special tokens dict
			__lowercase											=     {
			    self.pad_token: 0,
			    self.eos_token: 1,
			    self.unk_token: 2,
			}
			__lowercase											=     len(self.special_tokens_encoder   )
			__lowercase											=     len(__lowerCamelCase   )
			for i, token in enumerate(__lowerCamelCase   ):
					__lowercase											=     self.vocab_size + i - n
			__lowercase											=     {v: k for k, v in self.special_tokens_encoder.items()}




	@property
	def    UpperCAmelCase			(						self							:     Optional[int]   )       -> str:

			'''simple docstring'''




			return self._utf_vocab_size + self._num_special_tokens + self._extra_ids




	def    UpperCAmelCase			(						self							:     Tuple					,      __lowerCamelCase							:     List[int]					,      __lowerCamelCase							:     Optional[List[int]] = None					,      __lowerCamelCase							:     bool = False   )       -> List[int]:

			'''simple docstring'''




			if already_has_special_tokens:
					return super().get_special_tokens_mask(
					    token_ids_a=__lowerCamelCase					,      token_ids_a=__lowerCamelCase					,      already_has_special_tokens=__lowerCamelCase   )

			# normal case: some special tokens
			if token_ids_a is None:
					return ([0] * len(__lowerCamelCase   )) + [1]
			return ([0] * len(__lowerCamelCase   )) + [1] + ([0] * len(__lowerCamelCase   )) + [1]




	def    UpperCAmelCase			(						self							:     List[Any]					,      __lowerCamelCase							:     List[int]   )       -> List[int]:

			'''simple docstring'''




			if len(__lowerCamelCase   ) > 0 and token_ids[-1] == self.eos_token_id:
					warnings.warn(
					    F"This sequence already has {self.eos_token}. In future versions this behavior may lead to duplicated"
					    ' eos tokens being added.'   )
					return token_ids
			else:
					return token_ids + [self.eos_token_id]




	def    UpperCAmelCase			(						self							:     Optional[Any]					,      __lowerCamelCase							:     List[int]					,      __lowerCamelCase							:     Optional[List[int]] = None   )       -> List[int]:

			'''simple docstring'''




			__lowercase											=     [self.eos_token_id]

			if token_ids_a is None:
					return len(token_ids_a + eos   ) * [0]
			return len(token_ids_a + eos + token_ids_a + eos   ) * [0]




	def    UpperCAmelCase			(						self							:     Any					,      __lowerCamelCase							:     List[int]					,      __lowerCamelCase							:     Optional[List[int]] = None   )       -> List[int]:

			'''simple docstring'''




			__lowercase											=     self._add_eos_if_not_present(__lowerCamelCase   )
			if token_ids_a is None:
					return token_ids_a
			else:
					__lowercase											=     self._add_eos_if_not_present(__lowerCamelCase   )
					return token_ids_a + token_ids_a




	def    UpperCAmelCase			(						self							:     int					,      __lowerCamelCase							:     str   )       -> List[str]:

			'''simple docstring'''




			__lowercase											=     [chr(__lowerCamelCase   ) for i in text.encode('utf-8'   )]
			return tokens




	def    UpperCAmelCase			(						self							:     Dict					,      __lowerCamelCase							:     Dict   )       -> List[str]:

			'''simple docstring'''




			if token in self.special_tokens_encoder:
					__lowercase											=     self.special_tokens_encoder[token]
			elif token in self.added_tokens_encoder:
					__lowercase											=     self.added_tokens_encoder[token]
			elif len(__lowerCamelCase   ) != 1:
					__lowercase											=     self.unk_token_id
			else:
					__lowercase											=     ord(__lowerCamelCase   ) + self._num_special_tokens
			return token_id




	def    UpperCAmelCase			(						self							:     int					,      __lowerCamelCase							:     int   )       -> int:

			'''simple docstring'''




			if index in self.special_tokens_decoder:
					__lowercase											=     self.special_tokens_decoder[index]
			else:
					__lowercase											=     chr(index - self._num_special_tokens   )
			return token




	def    UpperCAmelCase			(						self							:     str					,      __lowerCamelCase							:     Dict   )       -> List[str]:

			'''simple docstring'''




			__lowercase											=     b""
			for token in tokens:
					if token in self.special_tokens_decoder:
							__lowercase											=     self.special_tokens_decoder[token].encode('utf-8'   )
					elif token in self.added_tokens_decoder:
							__lowercase											=     self.special_tokens_decoder[token].encode('utf-8'   )
					elif token in self.special_tokens_encoder:
							__lowercase											=     token.encode('utf-8'   )
					elif token in self.added_tokens_encoder:
							__lowercase											=     token.encode('utf-8'   )
					else:
							__lowercase											=     bytes([ord(__lowerCamelCase   )]   )
					bstring += tok_string
			__lowercase											=     bstring.decode('utf-8'					,      errors='ignore'   )
			return string






	def    UpperCAmelCase			(						self							:     List[Any]					,      __lowerCamelCase							:     str					,      __lowerCamelCase							:     Optional[str] = None   )       -> Tuple[str]:

			'''simple docstring'''




			return ()






import unittest

from transformers.testing_utils import require_bsa
from transformers.utils import is_bsa_available

from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin


if is_bsa_available():
		from transformers import MarkupLMFeatureExtractor




class 					lowerCamelCase__				(							unittest.TestCase):




	'''simple docstring'''




	def __init__(   self						:Optional[int]	,  a						:List[str]		)						->					Union[str, Any]:
								__UpperCamelCase      :  Dict       =   parent







	def   _lowerCamelCase							(   self						:Dict		)						->					int:
								return {}




def       _SCREAMING_SNAKE_CASE   (						)   ->       Optional[Any]:






							'''simple docstring'''





							__UpperCamelCase      :  Union[str, Any]       =   "<HTML>\n\n    <HEAD>\n    <TITLE>sample document</TITLE>\n    </HEAD>\n\n    <BODY BGCOLOR=\"FFFFFF\">\n    <HR>\n    <a href=\"http://google.com\">Goog</a>\n    <H1>This is one header</H1>\n    <H2>This is a another Header</H2>\n    <P>Travel from\n        <P>\n        <B>SFO to JFK</B>\n        <BR>\n        <B><I>on May 2, 2015 at 2:00 pm. For details go to confirm.com </I></B>\n        <HR>\n        <div style=\"color:#0000FF\">\n            <h3>Traveler <b> name </b> is\n            <p> John Doe </p>\n        </div>"

							__UpperCamelCase      :  Optional[int]       =   "\n    <!DOCTYPE html>\n    <html>\n    <body>\n\n    <h1>My First Heading</h1>\n    <p>My first paragraph.</p>\n\n    </body>\n    </html>\n    "

							return [html_string_a, html_string_a]




@require_bsa
class 					lowerCamelCase__				(							__lowercase	,		unittest.TestCase):




	'''simple docstring'''




	_A								=	MarkupLMFeatureExtractor if is_bsa_available() else None







	def   _lowerCamelCase							(   self						:List[str]		)						->					str:
								__UpperCamelCase      :  List[str]       =   MarkupLMFeatureExtractionTester(self		)







	@property
	def   _lowerCamelCase							(   self						:List[Any]		)						->					List[str]:
								return self.feature_extract_tester.prepare_feat_extract_dict()







	def   _lowerCamelCase							(   self						:Dict		)						->					Dict:
								# Initialize feature_extractor
								__UpperCamelCase      :  Tuple       =   self.feature_extraction_class()

								# Test not batched input
								__UpperCamelCase      :  Union[str, Any]       =   get_html_strings()[0]
								__UpperCamelCase      :  Any       =   feature_extractor(a		)

								# fmt: off
								__UpperCamelCase      :  Union[str, Any]       =   [["sample document", "Goog", "This is one header", "This is a another Header", "Travel from", "SFO to JFK", "on May 2, 2015 at 2:00 pm. For details go to confirm.com", "Traveler", "name", "is", "John Doe"]]
								__UpperCamelCase      :  Tuple       =   [["/html/head/title", "/html/body/a", "/html/body/h1", "/html/body/h2", "/html/body/p", "/html/body/p/p/b[1]", "/html/body/p/p/b[2]/i", "/html/body/p/p/div/h3", "/html/body/p/p/div/h3/b", "/html/body/p/p/div/h3", "/html/body/p/p/div/h3/p"]]
								# fmt: on

								self.assertEqual(encoding.nodes	,  a		)
								self.assertEqual(encoding.xpaths	,  a		)

								# Test batched
								__UpperCamelCase      :  str       =   get_html_strings()
								__UpperCamelCase      :  List[Any]       =   feature_extractor(a		)

								# fmt: off
								__UpperCamelCase      :  Optional[int]       =   expected_nodes + [["My First Heading", "My first paragraph."]]
								__UpperCamelCase      :  Tuple       =   expected_xpaths + [["/html/body/h1", "/html/body/p"]]

								self.assertEqual(len(encoding.nodes		)	,  2		)
								self.assertEqual(len(encoding.xpaths		)	,  2		)

								self.assertEqual(encoding.nodes	,  a		)
								self.assertEqual(encoding.xpaths	,  a		)